Data Science Hacks, Tips and Tricks

  • IntermediateLevel

  • 4 hrs 0 minsDuration

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About this Course

  • This course provides Python programming hacks, tips, and tricks to enhance efficiency in data science tasks, improving workflow and coding practices.
  • It covers essential data exploration hacks, enabling you to analyze datasets effectively, generate insights quickly, and streamline data understanding.
  • Designed for data scientists, analysts, and coding enthusiasts, this course helps improve efficiency by teaching optimized approaches to data science.

Learning Outcomes

Write Efficient Code

Learn Python tricks to optimize and improve data science workflow.

Explore Data Quickly

Use effective techniques to analyze datasets and gain insights.

Automate Data Tasks

Streamline workflows by automating repetitive tasks in Python.

Who Should Enroll

  • Data scientists aiming to write efficient code, streamline workflows, and improve models using advanced Python.
  • Data analysts seeking to enhance exploration, improve preprocessing, and optimize workflows for practical use.
  • Anyone eager to learn Python tips, automate tasks, and boost productivity with efficient coding techniques.

Course Curriculum

Explore a comprehensive curriculum covering Python, machine learning models, deep learning techniques, and AI applications.

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  1. 1. About the Data Science Hacks, Tips and Tricks Course

  2. 2. Course Overview and Learning Path

  3. 3. Setting Up Your Environment

  1. 1. AI&ML Blackbelt Plus Program (Sponsored)

  1. 1. Resource Downloader

  2. 2. Automated Data Collection

  3. 3. Web Scraping Techniques

  1. 1. Pandas Apply

  2. 2. Advanced Pandas Functions

  3. 3. Vectorization Techniques

  4. 4. Custom Apply Functions

  1. 1. How to extract email addresses from text?

  2. 2. Regular Expressions in Python

  3. 3. Text Pattern Matching

  1. 1. Automated Missing Value Handling

  2. 2. Outlier Detection Techniques

  3. 3. Streamlining Data Cleaning Workflows

  1. 1. Jupyter Notebook Efficiency Tips

  2. 2. Magic Commands

  3. 3. Notebook Extensions

  4. 4. Reproducible Notebooks

  1. 1. Rapid Data Visualization

  2. 2. Matplotlib Hacks

  3. 3. Interactive Plotting

  4. 4. Dashboard Creation

  1. 1. List Comprehensions

  2. 2. Generator Expressions

  3. 3. Lambda Functions

  4. 4. Decorators for Data Science

  1. 1. Quick Model Prototyping

  2. 2. Feature Selection Techniques

  3. 3. Cross-Validation Shortcuts

  4. 4. Model Interpretation Hacks

Projects you will build

Apply skills with hands-on projects.

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Data Exploration Automation

Build a reusable Python toolkit that automates common data exploration tasks, generates insightful visualizations, and creates automated data quality reports to streamline your workflow.

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Efficient Model Pipeline

Develop an end-to-end machine learning pipeline that implements the efficiency hacks learned throughout the course, focusing on preprocessing, feature engineering, and model selection automation.

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Kunal Jain

CEO, Analytics Vidhya

Kunal Jain, CEO of Analytics Vidhya, has 15+ years of experience in Data Science. He has guided thousands of professionals into data science careers through structured learning paths, industry insights, and hands-on training programs.

Get this Course Now

With this course you’ll get

  • 240 hour

    Duration

  • Kunal Jain

    Instructor

  • Intermediate

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility

Frequently Asked Questions

Looking for answers to other questions?

This course is for those who want to write efficient data science code, learn programming hacks, or explore useful tips

This course is completely free of cost!

You will have 6 months of access after registration. After that, you need to re-enroll, and past progress will be lost.

You can complete this course in a few hours. Each module is independent, allowing you to learn at your convenience.

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